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Simplify Big Data Analytics with Amazon EMR
Simplify Big Data Analytics with Amazon EMR

Simplify Big Data Analytics with Amazon EMR: A beginner's guide to learning and implementing Amazon EMR for building data analytics solutions

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Simplify Big Data Analytics with Amazon EMR

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Key benefits

  • Build data pipelines that require distributed processing capabilities on a large volume of data
  • Discover the security features of EMR such as data protection and granular permission management
  • Explore best practices and optimization techniques for building data analytics solutions in Amazon EMR

Description

Amazon EMR, formerly Amazon Elastic MapReduce, provides a managed Hadoop cluster in Amazon Web Services (AWS) that you can use to implement batch or streaming data pipelines. By gaining expertise in Amazon EMR, you can design and implement data analytics pipelines with persistent or transient EMR clusters in AWS. This book is a practical guide to Amazon EMR for building data pipelines. You'll start by understanding the Amazon EMR architecture, cluster nodes, features, and deployment options, along with their pricing. Next, the book covers the various big data applications that EMR supports. You'll then focus on the advanced configuration of EMR applications, hardware, networking, security, troubleshooting, logging, and the different SDKs and APIs it provides. Later chapters will show you how to implement common Amazon EMR use cases, including batch ETL with Spark, real-time streaming with Spark Streaming, and handling UPSERT in S3 Data Lake with Apache Hudi. Finally, you'll orchestrate your EMR jobs and strategize on-premises Hadoop cluster migration to EMR. In addition to this, you'll explore best practices and cost optimization techniques while implementing your data analytics pipeline in EMR. By the end of this book, you'll be able to build and deploy Hadoop- or Spark-based apps on Amazon EMR and also migrate your existing on-premises Hadoop workloads to AWS.

Who is this book for?

This book is for data engineers, data analysts, data scientists, and solution architects who are interested in building data analytics solutions with the Hadoop ecosystem services and Amazon EMR. Prior experience in either Python programming, Scala, or the Java programming language and a basic understanding of Hadoop and AWS will help you make the most out of this book.

What you will learn

  • Explore Amazon EMR features, architecture, Hadoop interfaces, and EMR Studio
  • Configure, deploy, and orchestrate Hadoop or Spark jobs in production
  • Implement the security, data governance, and monitoring capabilities of EMR
  • Build applications for batch and real-time streaming data analytics solutions
  • Perform interactive development with a persistent EMR cluster and Notebook
  • Orchestrate an EMR Spark job using AWS Step Functions and Apache Airflow

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Mar 25, 2022
Length: 430 pages
Edition : 1st
Language : English
ISBN-13 : 9781801077729
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Amazon
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Product Details

Publication date : Mar 25, 2022
Length: 430 pages
Edition : 1st
Language : English
ISBN-13 : 9781801077729
Vendor :
Amazon
Category :
Concepts :
Tools :

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Table of Contents

18 Chapters
Section 1: Overview, Architecture, Big Data Applications, and Common Use Cases of Amazon EMR Chevron down icon Chevron up icon
Chapter 1: An Overview of Amazon EMR Chevron down icon Chevron up icon
Chapter 2: Exploring the Architecture and Deployment Options Chevron down icon Chevron up icon
Chapter 3: Common Use Cases and Architecture Patterns Chevron down icon Chevron up icon
Chapter 4: Big Data Applications and Notebooks Available in Amazon EMR Chevron down icon Chevron up icon
Section 2: Configuration, Scaling, Data Security, and Governance Chevron down icon Chevron up icon
Chapter 5: Setting Up and Configuring EMR Clusters Chevron down icon Chevron up icon
Chapter 6: Monitoring, Scaling, and High Availability Chevron down icon Chevron up icon
Chapter 7: Understanding Security in Amazon EMR Chevron down icon Chevron up icon
Chapter 8: Understanding Data Governance in Amazon EMR Chevron down icon Chevron up icon
Section 3: Implementing Common Use Cases and Best Practices Chevron down icon Chevron up icon
Chapter 9: Implementing Batch ETL Pipeline with Amazon EMR and Apache Spark Chevron down icon Chevron up icon
Chapter 10: Implementing Real-Time Streaming with Amazon EMR and Spark Streaming Chevron down icon Chevron up icon
Chapter 11: Implementing UPSERT on S3 Data Lake with Apache Spark and Apache Hudi Chevron down icon Chevron up icon
Chapter 12: Orchestrating Amazon EMR Jobs with AWS Step Functions and Apache Airflow/MWAA Chevron down icon Chevron up icon
Chapter 13: Migrating On-Premises Hadoop Workloads to Amazon EMR Chevron down icon Chevron up icon
Chapter 14: Best Practices and Cost-Optimization Techniques Chevron down icon Chevron up icon
Other Books You May Enjoy Chevron down icon Chevron up icon

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Vishwa Apr 06, 2022
Full star icon Full star icon Full star icon Full star icon Full star icon 5
This book provides great in-depth and step by step guide to learn Amazon EMR which is the leading cloud big data platform. This book solves a gap by collating all the content in one location with regards to Big Data / Governance / Security using Amazon EMR and will significantly reduce time to learn and be expert in Amazon EMR.It's a MUST HAVE resource for big data architect / engineers working on AWS and Amazon EMR, also it's a great resource for organizations evaluation cloud big data options and want to dive deep into the capabilities of Amazon EMR.
Amazon Verified review Amazon
Rahul Apr 18, 2022
Full star icon Full star icon Full star icon Full star icon Full star icon 5
I have not gone deep into big data tech stack much but was always curious to learn more about it. Amazon EMR is one of the popular AWS service which provides managed Hadoop cluster on AWS but earlier I didn't find any single place that curates all the content in a structured manner for beginners to learn. This book I felt fills the gap as it starts from very basic and then dives deep into advanced concepts of EMR including security, data governance, best practices and cost optimization techniques. The best part I liked about the book is its explanation around EMR integration with other AWS services and how an end to end architecture look like if I need to build a data analytics pipeline on AWS.This book is kind of must to have for engineers and architects, who wants to dive deep into Hadoop/Spark based big data processing in AWS.
Amazon Verified review Amazon
Phani A Apr 05, 2022
Full star icon Full star icon Full star icon Full star icon Full star icon 5
This book provides plenty of thorough and detailed examples, insights, hands-on exercises from AWS Big Data architects and walks you through the patterns and strategies that will help you prepare to work on Big Data Analytics solutions with Amazon EMR. With easily relatable language, the examples and use cases provided in this book are not only accessible but very detailed. This book is divided into three sections and my favorite section working for AWS is the third section - Implementing common use cases and Best practices. This section covers most of the actual implementation examples and scenarios. Sakti has taken great care in providing detailed hands-on exercises for readers interested in trying out and implementing some of these solutions on AWS.I highly recommend it for any Big Data Engineer or Architects looking to implement Lakehouse, Data Lake and Big Data solutions on AWS. I also recommend readers reading each and every section at your own pace and then also keeping it on hand as a reference guide. The explanations are very detailed and clear, and the graphics are vibrant, eye-catching and work extremely well in support of each topic. The book is structured very well and uses bullet points and numbering to break down challenging concepts.
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Prashant Chaudhari Apr 30, 2022
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Highly recommend this book to all beginners who are new to data analytics in AWS.I am a beginner to big data analytics domain and this book gave me a great kick start to accelerate my learning. The first part of the book provides great theoretical details on big data, Amazon EMR features and its integration with other AWS services to implement different architecture patterns.The second and third parts dives deep into advance topics including security, data governance, orchestration, cost optimization etc. The best thing about the book is its practical examples to explain each topic that helped to relate things better.After reading this book, you will feel very confident about EMR and how to implement data pipelines in AWS.
Amazon Verified review Amazon
Naseer Sayyad Apr 12, 2022
Full star icon Full star icon Full star icon Full star icon Full star icon 5
I really enjoyed learning from this book, that has dived deep into Amazon EMR. Even if I had exposure to Big Data Hadoop & Spark, but learning how that relates to AWS cloud was a great value add for me. It covers the theoretical fundamentals for beginners and also practical use case based implementations for professionals that makes it really worth. It is really well researched and put together, the author has pen down his experience into it, which is what I liked the most compared to any other materials available in the internet.I would highly recommend this book to all data engineers and analysts who are getting started with Amazon EMR.
Amazon Verified review Amazon
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